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MiniMax M2.5

MiniMax M2.5

The first open model to beat Sonnet made for productivity

207upvotes
Launched February 17, 2026

About MiniMax M2.5

MiniMax M2.5 is a cutting-edge open-source AI model designed for enhanced productivity across a range of tasks. Built to outperform previous benchmarks like Sonnet, it delivers state-of-the-art performance in coding (SWE-Bench Verified 80.2%), search capabilities (BrowseComp 76.3%), and agentic tool-calling (BFCL 76.8%), making it an ideal choice for developers, researchers, and enterprise users. Its optimized architecture ensures 37% faster execution on complex tasks, enabling efficient handling of long-horizon workflows. With a competitive cost structure of around $1 per hour at 100 TPS, MiniMax M2.5 makes large-scale, scalable AI deployments economically feasible, opening new possibilities for autonomous agents and intensive automation. Its open-source nature encourages customization, transparency, and community-driven improvements, positioning it as a versatile and powerful tool in the AI ecosystem.

Screenshots

MiniMax M2.5 screenshot 1
MiniMax M2.5 screenshot 2
MiniMax M2.5 screenshot 3

Pros

  • SOTA performance across multiple benchmarks
  • Open-source, highly customizable
  • Significantly faster execution for complex tasks
  • Cost-effective at scale (around $1/hour at 100 TPS)
  • Ideal for long-horizon, autonomous workflows

Cons

  • Requires technical expertise for setup and customization
  • Limited out-of-the-box user-friendly features for non-developers
  • Dependence on infrastructure for scaling and deployment

Use Cases

1Automating complex coding and software development tasks
2Enhancing search and information retrieval workflows
3Powering autonomous AI agents for business automation
4Supporting research in AI and machine learning
5Building scalable, cost-effective AI solutions for enterprises
6Custom AI model deployment for specialized industry needs

Pricing

Open source with a pay-as-you-go model costing around $1 per hour at 100 TPS, making it accessible for large-scale deployment without significant upfront investment.

Quick Info

Upvotes207
Comments8
Launched2/17/2026

Topics

Open SourceSoftware EngineeringArtificial IntelligenceGitHub

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